Development of a Chemical Flood Simulator Based on Predictive HLD-NAC Equation of State for Surfactant

Abstract

Abstract Chemical flood reservoir simulators developed based on component partitioning model or empirical phase behavior model lack the effects of physical properties such as surfactant structure and oil properties i.e. equivalent alkane carbon number (EACN) on microemulsion phase behavior. Hence, these simulators have limited function in helping formulation design. A typical empirical microemulsion phase behavior model is the Hand's model that is used in UTCHEM, a benchmark chemical flood compositional simulator. However, it needs several matching parameters to fit phase behavior experiments and requires iterative calculations to solve phase compositions. Therefore, it is desirable to develop a chemical flood simulator with a more efficient and physics-based phase behavior model. This work incorporates a physics based HLD-NAC equation of state (EOS) into UTCHEM. A non-iterative flash calculation algorithm based on HLD-NAC microemulsion EOS is developed, which uses simple equations to represent plait point, binodal curve, and tie-lines. Input model parameters include quantitatively characterized physical properties, such as oil EACN, reservoir temperature, surfactant structure properties (head area and tail length), and optimum solubilization ratio. Therefore, the effects of these parameters on oil recovery can be systemically studied. Coreflood simulation results are validated against the Hand's model. Compared to the Hand's model which requires at least 5 matching parameters and with limited predictability, the HLD-NAC EOS can reproduce microemulsion phase behavior with surfactant tail length as the only fitting parameter. Comparing coreflood simulations using the HLD-NAC model and the Hand's model shows that the same oil recovery curves are obtained when slug at optimum salinity is injected. However, for corefloods using a salinity gradient design, HLD-NAC model predicts higher oil recovery than the Hand's model. The reasons for the differences are analyzed by examining the simulated solubilization ratios and ternary phase diagrams at different salinities. Moreover, numerical experiments show that the HLD-NAC model improves the phase behavior computational efficiency by approximately 65%. The effect of live oil at reservoir pressure is also investigated. Results indicate shifted optimal salinity and solubilization ratio due to solution gas and pressure lead to larger microemulsion bank. Owing to the physical significance, simplicity, and computational efficiency of the HLD-NAC EOS, this novel chemical flooding simulator proves to be a fast and promising tool to speed up surfactant screening process and helping chemical formulation development and injection designs.